Field of the Invention
This invention relates to health related data analysis and more particularly relates to a system and method for determination of temporal relationships between a desired attribute and any other attribute.
Description of the Related Art
Most corporations, including health insurance corporations, maintain a high volume of data. Such data may be analyzed and exploited for valuable information regarding business trends, and other important statistics. Data mining is a common strategy for identifying and analyzing such data.
There are many various forms of data mining. Custom analytic operations may be developed to meet specific needs. Alternatively, commercially available statistical analysis tools, such as Statistical Analysis Software (SAS) may be used to identify statistical trends in data.
Health insurance companies typically maintain databases of health insurance claim information, demographic information, and other data about health insurance plan members. Such information may be used to gain valuable insights into early disease diagnosis, relationship between lab tests and diseases or drug treatments, and disease severity. Unfortunately, typical methods for analyzing such data are often cumbersome, costly, and require unworkably high processing times and resources. For example, diseases often have pre-cursors and stages. Discovering these using existing methods requires time-consuming ad-hoc analysis.
The referenced shortcomings are not intended to be exhaustive, but rather are among many that tend to impair the effectiveness of previously known techniques in disease management, diagnosis and treatment; however, those mentioned here are sufficient to demonstrate that the methodologies appearing in the art have not been satisfactory and that a significant need exists for the techniques described and claimed in this disclosure.